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This paper is in the following e-collection/theme issue:

Digital Health Reviews (3461) Theoretical Frameworks and Concepts (499) Machine Learning (2996) Artificial Intelligence (4462) Applications of AI (808)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66559, first published .
Healthcare professionals working at computers in a modern clinic

Maturity Framework for Operationalizing Machine Learning Applications in Health Care: Scoping Review

Maturity Framework for Operationalizing Machine Learning Applications in Health Care: Scoping Review

Authors of this article:

Yutong Li1 Author Orcid Image ;   Julie Tian1 Author Orcid Image ;   Ariana Xu1 Author Orcid Image ;   Russell Greiner2 Author Orcid Image ;   Jake Hayward3 Author Orcid Image ;   Andrew James Greenshaw1 Author Orcid Image ;   Bo Cao1 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

Journals

  1. Gozum I. Conscience, Care, and Code: Moral Theology, AI, and Ethical Decision-Making at the Thresholds of Life. Journal of Religion and Health 2026 View
  2. Chavarro J, Gómez García M, Alcaide Leyva J, Martínez Gutiérrez A, Zambrano Bermeo R. Identification of Predictors of Adaptability in Older Adults Based on the Roy Adaptation Model Using Machine Learning. Journal of Clinical Medicine 2026;15(5):1709 View
  3. Saraboji K, Gopalakrishnan K, Sood D, Kaur A, Shivaram S, Helgeson S, Arunachalam S, Mitra D. Operationalizing WHO Ethical Principles for Healthcare AI: A Lifecycle-Aligned Governance-by-Design Framework. AI in Medicine 2026;1(2):16 View
  4. Cabitza F, Jurman G, Molinari F, Bellazzi R. Why almost all ML models for medicine are wrong-and what we need for evidence-based medical AI. International Journal of Medical Informatics 2026;219:106538 View